A ground-based 21cm Baryon acoustic oscillation survey

Baryon acoustic oscillations (BAO) provide a robust standard ruler with which to measure the acceleration of the Universe. The BAO feature has so far been detected in optical galaxy surveys. Intensity mapping of neutral hydrogen emission with a ground-based radio telescope provides another promising window for measuring BAO at redshifts of order unity for relatively low cost. While the cylindrical radio telescope (CRT) proposed for these measurements will have excellent redshift resolution, it will suffer from poor angular resolution (a few arcminutes at best). We investigate the effect of angular resolution on the standard ruler test with BAO, using the Dark Energy Task Force Figure of Merit as a benchmark. We then extend the analysis to include variations in the parameters characterizing the telescope and the underlying physics. Finally, we optimize the survey parameters (holding total cost fixed) and present an example of a CRT BAO survey that is competitive with Stage III dark energy experiments. The tools developed here form the backbone of a publicly available code that can be used to obtain estimates of cost and Figure of Merit for any set of parameters.Comment: ApJ accepted version. Important changes in section 2 and 3 - uses a more realistic instrument response model and removed the discussion of aliasing effect. The conclusions remain the same. Typos fixed (including eq 5). 11 emulated apj pages with 7 figures and 1 tabl

Validation of the Organizational Culture Assessment Instrument: An Application of the Korean Version

The purpose of this study was to examine the psychometric properties of the Korean version of the Organizational Culture Assessment Instrument (OCAI) based on the Competing Values Framework (CVF). More specially, cultural equivalence between the Korean version and the original English version of the OCAI was evaluated using 39 bilingual Koreans. Next, a field test was conducted to examine scale reliability and construct validity of the Korean version of the OCAI using 133 organizational members from the Korean Professional Baseball League (KPBL). The findings indicate that the Korean version was successfully translated, items maintained the same meaning of the original OCAI items, and yielded acceptable psychometric properties making it applicable to Korean sport organizations

Atroposelective Synthesis of PINAP via Dynamic Kinetic Asymmetric Transformation

The atroposelective synthesis of PINAP ligands has been accomplished via a palladium‐catalyzed C−P coupling process through dynamic kinetic asymmetric transformation. These catalytic conditions allow access to a wide variety of alkoxy‐ and benzyloxy‐substituted PINAP ligands in high enantiomeric excess. The methods described in this communication afford valuable P,N ligands in good yields and high enantioselectivity using low catalyst loading

TransNets: Learning to Transform for Recommendation

Recently, deep learning methods have been shown to improve the performance of recommender systems over traditional methods, especially when review text is available. For example, a recent model, DeepCoNN, uses neural nets to learn one latent representation for the text of all reviews written by a target user, and a second latent representation for the text of all reviews for a target item, and then combines these latent representations to obtain state-of-the-art performance on recommendation tasks. We show that (unsurprisingly) much of the predictive value of review text comes from reviews of the target user for the target item. We then introduce a way in which this information can be used in recommendation, even when the target user's review for the target item is not available. Our model, called TransNets, extends the DeepCoNN model by introducing an additional latent layer representing the target user-target item pair. We then regularize this layer, at training time, to be similar to another latent representation of the target user's review of the target item. We show that TransNets and extensions of it improve substantially over the previous state-of-the-art.Comment: Accepted for publication in the 11th ACM Conference on Recommender Systems (RecSys 2017

A Spatial-dynamical Framework For Evaluation Of Satellite Rainfall Products For Flood Prediction

Rainfall maps that are derived from satellite observations provide hydrologists with an unprecedented opportunity to forecast floods globally. However, the limitation of using these precipitation estimates with respect to producing reliable flood forecasts at multiple scales are not well understood. To address the scientific and practical question of applicability of space-based rainfall products for global flood forecasting, a data evaluation framework is developed that allows tracking the rainfall effects in space and time across scales in the river network. This provides insights on the effects of rainfall product resolution and uncertainty. Obtaining such insights is not possible when the hydrologic evaluation is based on discharge observations from single gauges. The proposed framework also explores the ability of hydrologic model structure to answer questions pertaining to the utility of space-based rainfall observations for flood forecasting. To illustrate the framework, hydrometeorological data collected during the Iowa Flood Studies (IFloodS) campaign in Iowa are used to perform a hydrologic simulation using two different rainfall-runoff model structures and three rainfall products, two of which are radar based [stage IV and Iowa Flood Center (IFC)] and one satellite based [TMPA-Research Version (RV)]. This allows for exploring the differences in rainfall estimates at several spatial and temporal scales and provides improved understanding of how these differences affect flood predictions at multiple basin scales. The framework allows for exploring the differences in peak flow estimation due to nonlinearities in the hydrologic model structure and determining how these differences behave with an increase in the upstream area through the drainage network. The framework provides an alternative evaluation of precipitation estimates, based on the diagnostics of hydrological model results

Wavefront sensing and control performance modeling of the Thirty Meter telescope for systematic trade analyses

We have developed an integrated optical model of the semi-static performance of the Thirty Meter Telescope. The model includes surface and rigid body errors of all telescope optics as well as a model of the Alignment and Phasing System Shack-Hartmann wavefront sensors and control algorithms. This integrated model allows for simulation of the correction of the telescope wavefront, including optical errors on the secondary and tertiary mirrors, using the primary mirror segment active degrees of freedom. This model provides the estimate of the predicted telescope performance for system engineering and error budget development. In this paper we present updated performance values for the TMT static optical errors in terms of Normalized Point Source Sensitivity and RMS wavefront error after Adaptive Optics correction. As an example of a system level trade, we present the results from an analysis optimizing the number of Shack-Hartmann lenslets per segment. We trade the number of lenslet rings over each primary mirror segment against the telescope performance metrics of PSSN and RMS wavefront error

Probablistic Rainfall Forecasting Using Single-Valued Rainfall Forecasts for Risk-Based Water Management at the South Florida Water Management District

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv